STC1 regulates glioblastoma migration and invasion via the TGF‑β/SMAD4 signaling pathway

Stanniocalcin-1 promotes temozolomide resistance of glioblastoma through regulation of MGMT

Temozolomide (TMZ) resistance is a major challenge in the treatment of glioblastoma (GBM). Tumour reproductive cells (TRCs) have been implicated in the development of chemotherapy resistance. By culturing DBTRG cells in three-dimensional soft fibrin gels to enrich GBM TRCs and performing RNA-seq analysis, the expression of stanniocalcin-1 (STC), a gene encoding a secreted glycoprotein, was found to be upregulated in TRCs. Meanwhile, the viability of TMZ-treated TRC cells was significantly higher than that of TMZ-treated 2D cells. Analysis of clinical data from CGGA (Chinese Glioma Genome Atlas) database showed that high expression of STC1 was closely associated with poor prognosis, glioma grade and resistance to TMZ treatment, suggesting that STC1 may be involved in TMZ drug resistance. The expression of STC1 in tissues and cells was examined, as well as the effect of STC1 on GBM cell proliferation and TMZ-induced DNA damage. The results showed that overexpression of STC1 promoted and knockdown of STC1 inhibited TMZ-induced DNA damage. These results were validated in an intracranial tumour model. These data revealed that STC1 exerts regulatory functions on MGMT expression in GBM, and provides a rationale for targeting STC1 to overcome TMZ resistance.

A signature based on circadian rhythm-associated genes for the evaluation of prognosis and the tumour microenvironment in HNSCC

The morbidity and mortality rates of head and neck squamous cell carcinoma (HNSCC) remain high worldwide. Therefore, there is an urgent need to identify a new prognostic biomarker to guide the personalized treatment of HNSCC patients. Increasing evidence suggests that circadian rhythm genes play an important role in the development and progression of cancer. We aimed to explore the value of circadian rhythm genes in predicting prognosis and guiding the treatment of HNSCC. We first obtained a list of circadian rhythm genes from previous research. The sequencing data were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Finally, univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox proportional hazard analysis were performed to develop a prognostic signature (Circadian Rhythm-Related Gene Prognostic Index, CRRGPI) consisting of nine circadian rhythm genes. The signature exhibited good performance in predicting overall survival. Patients with low CRRGPI scores had lower metabolic activities and an active antitumour immunity ability. Additionally, a clinical cohort was used to further evaluate the ability of the CRRGPI to predict the efficacy of immune checkpoint inhibitors. In conclusion, the novel circadian rhythm-related gene signature can provide a precise prognostic evaluation with the potential capacity to guide individualized treatment regimens for HNSCC patients.

Hypoxia drives shared and distinct transcriptomic changes in two invasive glioma stem cell lines

Glioblastoma (GBM) is the most common primary malignant cancer of the central nervous system. Insufficient oxygenation (hypoxia) has been linked to GBM invasion and aggression, leading to poor patient outcomes. Hypoxia induces gene expression for cellular adaptations. However, GBM is characterized by high intertumoral (molecular subtypes) and intratumoral heterogeneity (cell states), and it is not well understood to what extent hypoxia triggers patient-specific gene responses and cellular diversity in GBM. Here, we surveyed eight patient-derived GBM stem cell lines for invasion phenotypes in 3D culture, which identified two GBM lines showing increased invasiveness in response to hypoxia. RNA-seq analysis of the two patient GBM lines revealed a set of shared hypoxia response genes concerning glucose metabolism, angiogenesis, and autophagy, but also a large set of patient-specific hypoxia-induced genes featuring cell migration and anti-inflammation, highlighting intertumoral diversity of hypoxia responses in GBM. We further applied the Shared GBM Hypoxia gene signature to single cell RNA-seq datasets of glioma patients, which showed that hypoxic cells displayed a shift towards mesenchymal-like (MES) and astrocyte-like (AC) states. Interestingly, in response to hypoxia, tumor cells in IDH-mutant gliomas displayed a strong shift to the AC state, whereas tumor cells in IDH-wildtype gliomas mainly shifted to the MES state. This distinct hypoxia response of IDH-mutant gliomas may contribute to its more favorable prognosis. Our transcriptomic studies provide a basis for future approaches to better understand the diversity of hypoxic niches in gliomas.

Development of a prognostic model for glioblastoma multiforme based on the expression levels of efferocytosis-related genes

Glioblastoma multiforme (GBM) is one of the most common and aggressive brain tumors. The microenvironment of GBM is characterized by its highly immunosuppressive nature with infiltration of immunosuppressive cells and the expression levels of cytokines. Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. Efferocytosis plays a noticeable function in the formation of immunosuppressive environment. This study aimed to develop an efferocytosis-related prognostic model for GBM. The bioinformatic methods were utilized to analyze the transcriptomic data of GBM and normal samples. Clinical and RNA-seq data were sourced from TCGA database comprising 167 tumor samples and 5 normal samples, and 167 tumor samples for which survival information was available. Transcriptomic data of 1034 normal samples were collected from the Genotype-Tissue Expression (GTEx) database as a control sample supplement to the TCGA database. In the end, 167 tumor samples and 1039 normal samples were obtained for transcriptome analysis. Efferocytosis-related differentially expressed genes (ERDEGs) were obtained by intersecting 7487 differentially expressed genes (DEGs) between GBM and normal samples along with 1189 hub genes. Functional enrichment analyses revealed that ERDEGs were mainly involved in cytokine-mediated immune responses. Moreover, 9 prognosis-related genes (PRGs) were identified by the least absolute shrinkage and selection operator (LASSO) regression analysis, and a prognostic model was therefore developed. The nomogram combining age and risk score could effectively predict GBM patients' prognosis. GBM patients in the high-risk group had higher immune infiltration, invasion, epithelial-mesenchymal transition, angiogenesis scores and poorer tumor purity. In addition, the high-risk group exhibited higher half maximal inhibitory concentration (IC50) values for temozolomide, carmustine, and vincristine. Expression analysis indicated that PRGs were overexpressed in GBM cells. PDIA4 knockdown reduced efferocytosis in vitro. In summary, the proposed prognostic model for GBM based on efferocytosis-related genes exhibited a robust performance.

Exploring the anti-aging effects of fisetin in telomerase-deficient progeria mouse model

Aging is a natural and complex process characterized by the gradual deterioration of tissue and physiological functions in the organism over time. Cell senescence, a hallmark of aging, refers to the permanent and irreversible cell cycle arrest of proliferating cells triggered by endogenous stimuli or environmental stresses. Eliminating senescent cells has been shown to extend the healthy lifespan. In this study, we established a progeria mouse model with telomerase deficiency and confirmed the presence of shortened telomere length and increased expression of aging markers p16INK4a and p21CIP1 in the organ tissues of G3 Tert-/- mice. We identified fisetin as a potent senolytic drug capable of reversing premature aging signs in telomerase-deficient mice. Fisetin treatment effectively suppressed the upregulation of aging markers p16INK4a and p21CIP1 and reduced collagen fiber deposition. Furthermore, we observed a significant elevation in the mRNA level of Stc1 in G3Tert-/- mice, which was reduced after fisetin treatment. Stc1 has been implicated in anti-apoptotic processes through the upregulation of the Akt signaling pathway. Our findings reveal that fisetin exerts its anti-aging effect by inhibiting the Akt signaling pathway through the suppression of Stc1 expression, leading to the apoptosis of senescent cells.

LncBIRC3-OT promotes the malignant progression of glioma by interacting with RELA to upregulate stanniocalcin-1 expression

Glioma is the most common malignant intracranial tumor, accounting for 80 % of all malignant brain tumors. Growing evidence suggests that lncRNAs are involved in the growth, angiogenesis, metastasis, and therapeutic resistance in a variety of tumors, including glioma. In this study, lncBIRC3-OT (NONHSAT159592.1), which is highly expressed in glioma, was screened by RNA-seq method and verified by quantitative reverse transcription polymerase chain reaction. Subsequently, we knocked down the endogenous expression of lncBIRC3-OT in U87 and U251 cells and found that down-regulated lncBIRC3-OT inhibited cell proliferation, colony formation, migration, and invasion. Mechanically, lncBIRC3-OT could guide RELA protein to the stanniocalcin-1 (STC1) promoter, initiate STC1 transcription, and ultimately promote the progression of glioma. Together, these findings suggest that lncBIRC3-OT is an important regulator promoting glioma progression, and may be a promising therapeutic target for glioma.

TGF-β based risk model to predict the prognosis and immune features in glioblastoma

Background

Transforming growth factor-β (TGF-β) is a multifunctional cytokine with an important role in tissue development and tumorigenesis. TGF-β can inhibit the function of many immune cells, prevent T cells from penetrating into the tumor center, so that the tumor cells escape from immune surveillance and lead to low sensitivity to immunotherapy. However, its potential roles in predicting clinical prognosis and tumor microenvironment (TME) immune features need to be deeply investigated in glioblastoma (GBM).

Methods

The TCGA-GBM dataset was obtained from the Cancer Genome Atlas, and the validation dataset was downloaded from Gene Expression Omnibus. Firstly, differentially expressed TGF-β genes (DEGs) were screened between GBM and normal samples. Then, univariate and multivariate Cox analyses were used to identify prognostic genes and develop the TGF-β risk model. Subsequently, the roles of TGF-β risk score in predicting clinical prognosis and immune characteristics were investigated.

Results

The TGF-β risk score signature with an independent prognostic value was successfully developed. The TGF-β risk score was positively correlated with the infiltration levels of tumor-infiltrating immune cells, and the activities of anticancer immunity steps. In addition, the TGF-β risk score was positively related to the expression of immune checkpoints. Besides, the high score indicated higher sensitivity to immune checkpoint inhibitors.

Conclusions

We first developed and validated a TGF-β risk signature that could predict the clinical prognosis and TME immune features for GBM. In addition, the TGF-β signature could guide a more personalized therapeutic approach for GBM.

Cancer-associated mesothelial cell-derived ANGPTL4 and STC1 promote the early steps of ovarian cancer metastasis

Ovarian cancer (OvCa) preferentially metastasizes in association with mesothelial cell-lined surfaces. We sought to determine if mesothelial cells are required for OvCa metastasis and detect alterations in mesothelial cell gene expression and cytokine secretion upon interaction with OvCa cells. Using omental samples from patients with high-grade serous OvCa and mouse models with Wt1-driven GFP-expressing mesothelial cells, we validated the intratumoral localization of mesothelial cells during human and mouse OvCa omental metastasis. Removing mesothelial cells ex vivo from human and mouse omenta or in vivo using diphtheria toxin-mediated ablation in Msln-Cre mice significantly inhibited OvCa cell adhesion and colonization. Human ascites induced angiopoietin-like 4 (ANGPTL4) and stanniocalcin 1 (STC1) expression and secretion by mesothelial cells. Inhibition of STC1 or ANGPTL4 via RNAi obstructed OvCa cell-induced mesothelial cell to mesenchymal transition while inhibition of ANGPTL4 alone obstructed OvCa cell-induced mesothelial cell migration and glycolysis. Inhibition of mesothelial cell ANGPTL4 secretion via RNAi prevented mesothelial cell-induced monocyte migration, endothelial cell vessel formation, and OvCa cell adhesion, migration, and proliferation. In contrast, inhibition of mesothelial cell STC1 secretion via RNAi prevented mesothelial cell-induced endothelial cell vessel formation and OvCa cell adhesion, migration, proliferation, and invasion. Additionally, blocking ANPTL4 function with Abs reduced the ex vivo colonization of 3 different OvCa cell lines on human omental tissue explants and in vivo colonization of ID8p53-/-Brca2-/- cells on mouse omenta. These findings indicate that mesothelial cells are important to the initial stages of OvCa metastasis and that the crosstalk between mesothelial cells and the tumor microenvironment promotes OvCa metastasis through the secretion of ANGPTL4.

Effects and prognostic values of miR-30c-5p target genes in gastric cancer via a comprehensive analysis using bioinformatics

Gastric cancer (GC) is a common cancer and the leading cause of cancer-related death worldwide. To improve the diagnosis and treatment of GC, it is necessary to identify new biomarkers by investigating the cellular and molecular mechanisms. In this study, miR-30c-5p expression was significantly down-regulated in GC tissues by comprehensive analysis using multiple databases. The target genes of miR-30c-5p with up-regulated expression level in GC were identified, including ADAM12 (a disintegrin and metalloproteinase12), EDNRA (the Endothelin receptor type A), STC1 (stanniocalcin 1), and CPNE8 (the calcium-dependent protein, copine 8). The expression level of ADAM12 was significantly related to depth of invasion (p = 0.036) in GC patients. The expression level of EDNRA was significantly related to grade (P = 0.003), depth of invasion (P = 0.019), and lymphatic metastasis (P = 0.001). The expression level of CPNE8 was significantly related to grade (P = 0.043) and TNM stage (P = 0.027).Gene set enrichment analysis showed that they might participate in GC progression through cancer-related pathways. CIBERSORT algorithm analysis showed that their expressions were related to a variety of tumor-infiltrating immune cells. The higher expression of those target genes might be the independent risk factor for poor survival of GC patients, and they might be potential prognostic markers in GC patients.

RGC-32 Acts as a Hub to Regulate the Transcriptomic Changes Associated With Astrocyte Development and Reactive Astrocytosis

Response Gene to Complement 32 (RGC-32) is an important mediator of the TGF-β signaling pathway, and an increasing amount of evidence implicates this protein in regulating astrocyte biology. We showed recently that spinal cord astrocytes in mice lacking RGC-32 display an immature phenotype reminiscent of progenitors and radial glia, with an overall elongated morphology, increased proliferative capacity, and increased expression of progenitor markers when compared to their wild-type (WT) counterparts that make them incapable of undergoing reactive changes during the acute phase of experimental autoimmune encephalomyelitis (EAE). Here, in order to decipher the molecular networks underlying RGC-32's ability to regulate astrocytic maturation and reactivity, we performed next-generation sequencing of RNA from WT and RGC-32 knockout (KO) neonatal mouse brain astrocytes, either unstimulated or stimulated with the pleiotropic cytokine TGF-β. Pathway enrichment analysis showed that RGC-32 is critical for the TGF-β-induced up-regulation of transcripts encoding proteins involved in brain development and tissue remodeling, such as axonal guidance molecules, transcription factors, extracellular matrix (ECM)-related proteins, and proteoglycans. Our next-generation sequencing of RNA analysis also demonstrated that a lack of RGC-32 results in a significant induction of WD repeat and FYVE domain-containing protein 1 (Wdfy1) and stanniocalcin-1 (Stc1). Immunohistochemical analysis of spinal cords isolated from normal adult mice and mice with EAE at the peak of disease showed that RGC-32 is necessary for the in vivo expression of ephrin receptor type A7 in reactive astrocytes, and that the lack of RGC-32 results in a higher number of homeodomain-only protein homeobox (HOPX)+ and CD133+ radial glia cells. Collectively, these findings suggest that RGC-32 plays a major role in modulating the transcriptomic changes in astrocytes that ultimately lead to molecular programs involved in astrocytic differentiation and reactive changes during neuroinflammation.

Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer

Objectives

This study aimed to develop and validate a hypoxia signature for predicting survival outcomes in patients with bladder cancer.

Methods

We downloaded the RNA sequence and the clinicopathologic data of the patients with bladder cancer from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/repository?facetTab=files) and the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. Hypoxia genes were retrieved from the Molecular Signatures Database (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp). Differentially expressed hypoxia-related genes were screened by univariate Cox regression analysis and Lasso regression analysis. Then, the selected genes constituted the hypoxia signature and were included in multivariate Cox regression to generate the risk scores. After that, we evaluate the predictive performance of this signature by multiple receiver operating characteristic (ROC) curves. The CIBERSORT tool was applied to investigate the relationship between the hypoxia signature and the immune cell infiltration, and the maftool was used to summarize and analyze the mutational data. Gene-set enrichment analysis (GSEA) was used to investigate the related signaling pathways of differentially expressed genes in both risk groups. Furthermore, we developed a model and presented it with a nomogram to predict survival outcomes in patients with bladder cancer.

Results

Eight genes (AKAP12, ALDOB, CASP6, DTNA, HS3ST1, JUN, KDELR3, and STC1) were included in the hypoxia signature. The patients with higher risk scores showed worse overall survival time than the ones with lower risk scores in the training set (TCGA) and two external validation sets (GSE13507 and GSE32548). Immune infiltration analysis showed that two types of immune cells (M0 and M1 macrophages) had a significant infiltration in the high-risk group. Tumor mutation burden (TMB) analysis showed that the risk scores between the wild types and the mutation types of TP53, MUC16, RB1, and FGFR3 were significantly different. Gene-Set Enrichment Analysis (GSEA) showed that immune or cancer-associated pathways belonged to the high-risk groups and metabolism-related signal pathways were enriched into the low-risk group. Finally, we constructed a predictive model with risk score, age, and stage and validated its performance in GEO datasets.

Conclusion

We successfully constructed and validated a novel hypoxia signature in bladder cancer, which could accurately predict patients’ prognosis.

The Role of Network Science in Glioblastoma

Network science has long been recognized as a well-established discipline across many biological domains. In the particular case of cancer genomics, network discovery is challenged by the multitude of available high-dimensional heterogeneous views of data. Glioblastoma (GBM) is an example of such a complex and heterogeneous disease that can be tackled by network science. Identifying the architecture of molecular GBM networks is essential to understanding the information flow and better informing drug development and pre-clinical studies. Here, we review network-based strategies that have been used in the study of GBM, along with the available software implementations for reproducibility and further testing on newly coming datasets. Promising results have been obtained from both bulk and single-cell GBM data, placing network discovery at the forefront of developing a molecularly-informed-based personalized medicine.

Targeting POLE2 Creates a Novel Vulnerability in Renal Cell Carcinoma via Modulating Stanniocalcin 1

Objective

The aim of this study is to investigate the biological functions and the underlying mechanisms of DNA polymerase epsilon subunit 2 (POLE2) in renal cell carcinoma (RCC).

Methods

The datasets of POLE2 expression in The Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC) and International Cancer Genome Consortium (ICGC) databases was selected and the correlation between POLE2 and various clinicopathological parameters was analyzed. The POLE2 expression in RCC tissues was examined by immunohistochemistry. The POLE2 knockdown cell lines were constructed. In vitro and in vivo experiments were carried out to investigate the function of POLE2 on cellular biology of RCC, including cell viability assay, clone formation assay, flow cytometry, wound-healing assay, Transwell assay, qRT-PCR, Western blot, etc. Besides, microarray, co-immunoprecipitation, rescue experiment, and Western blot were used to investigate the molecular mechanisms underlying the functions of POLE2.

Results

POLE2 was overexpressed in RCC tissues, and high expression of POLE2 was correlated with poor prognosis of RCC. Furthermore, knockdown of POLE2 significantly inhibited cell proliferation, migration, and facilitated apoptosis in vitro. In vivo experiments revealed that POLE2 attenuated RCC tumorigenesis and tumor growth. we also illuminated that stanniocalcin 1 (STC1) was a downstream gene of POLE2, which promoted the occurrence and development of RCC. Besides, knockdown of POLE2 significantly upregulated the expression levels of Bad and p21 while the expression levels of HSP70, IGF-I, IGF-II, survivin, and sTNF-R1 were significantly downregulated. Western blot analysis also showed that knockdown of POLE2 inhibited the expression levels of Cancer-related pathway proteins including p-Akt, CCND1, MAPK9, and PIK3CA.

Conclusion

Knockdown of POLE2 attenuates RCC cells proliferation and migration by regulating STC1, suggesting that POLE2-STC1 may become a potential target for RCC therapy.

Identifying Predictive Gene Expression and Signature Related to Temozolomide Sensitivity of Glioblastomas

Temozolomide (TMZ) is considered a standard chemotherapeutic agent for glioblastoma (GBM). Characterizing the biological molecules and signaling pathways involved in TMZ sensitivity would be helpful for selecting therapeutic schemes and evaluating prognosis for GBM. Thus, in the present study, we selected 34 glioma cell lines paired with specific IC₅₀ values of TMZ obtained from CancerRxGene and RNA-seq data downloaded from the Cancer Cell Line Encyclopedia to identify genes related to TMZ sensitivity. The results showed that 1,373 genes were related to the response of GBM cells to TMZ. Biological function analysis indicated that epithelial–mesenchymal transition, Wnt signaling, and immune response were the most significantly activated functions in TMZ-resistant cell lines. Additionally, negative regulation of telomere maintenance via telomerase was enriched in TMZ-sensitive glioma cell lines. We also preliminarily observed a synergistic effect of combination treatment comprising TMZ and a telomerase inhibitor in vitro. We identified six genes (MROH8, BET1, PTPRN2, STC1, NKX3-1, and ARMC10) using the random survival forests variable hunting algorithm based on the minimum error rate of the gene combination and constructed a gene expression signature. The signature was strongly related to GBM clinical characteristics and exhibited good prognosis accuracy for both The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Patients in the high score group had a shorter survival time than those in the low score group (11.2 vs. 22.2 months, hazard ratio = 7.31, p = 4.59e−11) of the TCGA dataset. The CGGA dataset was selected as a validation group with 40 patients in the high score set and 43 patients in the low score set (12.5 vs. 28.8 months, hazard ratio = 3.42, p = 8.61e−5). Moreover, the signature showed a better prognostic value than MGMT promoter methylation in both datasets. We also developed a nomogram for clinical use that integrated the TMZ response signature and four other risk factors to individually predict patient survival after TMZ chemotherapy. Overall, our study provides promising therapeutic targets and potential guidance for adjuvant therapy of GBM.